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周璐, 徐世明, 曾刚. 20世纪90年代以来北极海冰减少的热动力分析——基于PIOMAS模式结果[J]. 大气科学, 2017, 41(1): 57-70. DOI: 10.3878/j.issn.1006-9895.1606.15267
引用本文: 周璐, 徐世明, 曾刚. 20世纪90年代以来北极海冰减少的热动力分析——基于PIOMAS模式结果[J]. 大气科学, 2017, 41(1): 57-70. DOI: 10.3878/j.issn.1006-9895.1606.15267
Lu ZHOU, Shiming XU, Gang ZENG. Dynamic and Thermodynamic Analysis of Arctic Sea Ice Decrease since the 1990s Based on PIOMAS Simulations[J]. Chinese Journal of Atmospheric Sciences, 2017, 41(1): 57-70. DOI: 10.3878/j.issn.1006-9895.1606.15267
Citation: Lu ZHOU, Shiming XU, Gang ZENG. Dynamic and Thermodynamic Analysis of Arctic Sea Ice Decrease since the 1990s Based on PIOMAS Simulations[J]. Chinese Journal of Atmospheric Sciences, 2017, 41(1): 57-70. DOI: 10.3878/j.issn.1006-9895.1606.15267

20世纪90年代以来北极海冰减少的热动力分析——基于PIOMAS模式结果

Dynamic and Thermodynamic Analysis of Arctic Sea Ice Decrease since the 1990s Based on PIOMAS Simulations

  • 摘要: 本文利用美国华盛顿大学的PIOMAS海冰模式输出结果,分析了20世纪90年代以来北极海冰减少的动力和热力过程的特征,并探讨了海冰减少与北极大气环流模态之间的关系。结果表明:(1)通过弗拉姆海峡输出的多年冰的厚度自1995年以来有显著减少;(2)海冰的热力过程在20世纪90年代以后特别是21世纪以来是海冰减少的主导因素;(3)大气模态中的北极涛动(AO)和北极偶极子(AD)均对北极海冰的动力输出有影响,各自与海冰输出量的相关关系显著,并且AO和AD的多元线性回归能很好的拟合出海冰输出量的减少。

     

    Abstract: Based on simulations from PIOMAS (Pan-Arctic Ice Ocean Modeling and Assimilation System) model developed by University of Washington and their comparison with observational data, this study analyzes the characteristic dynamic and thermodynamic processes of the decrease in Arctic sea ice. The sea ice volume output flux is used to study dynamic process while thermodynamic process is obtained from dynamics indirectly in the recent 30 years, especially since the 1990s. The correlations between the Arctic sea ice decrease and atmospheric circulation modes like Arctic Oscillation (AO) and Arctic Dipole (AD) are also discussed. Results show that the thickness of perennial sea ice over Fram Strait experienced a significant reduction since 1995. Thermodynamic process played a prominent role in the Arctic sea ice decrease since the 1990s, especially in the 2000s. Furthermore, AO and AD do have influences on the flux of Arctic sea ice volume and their correlations with the flux are all significant at the 99% confidence level. Multiple linear regression using AO and AD can fit the reduction of sea ice volume output flux perfectly.

     

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